1. Field of the Invention
The present invention relates to an image processing device which converts a blur state within an image.
2. Description of the Related Art
A general method of restoring degraded image data is assumed to be executed in a circumstance that satisfies at least one of the following conditions (1) to (4).
(1) A point-spread function (PSF) of input degraded image data is uniform (for example, Document 1: U.S. Pat. No. 6,859,564, Document 2: U.S. Pat. No. 5,561,611, and Document 3: U.S. Pat. No. 6,154,574).
(2) The PSF for the degraded image data is not uniform but varies slowly (for example, Document 4: M. K. Ozkan, A. M. Tekalp, and M. I. Sezan. Identification of a class of space-variant image blurs, Proc. SPIE 1452, 146-156, 1991).
(3) The PSF is available from sources a path (for example, a prior knowledge, a sensor, or the like) other than the degraded image data (for example, Document 5: U.S. Pat. No. 5,790,709, Document 6: J. M. Biouca-Dias. Bayesian wavelet-based image deconvolution: a GEM algorithm exploiting a class of heavy-tailored priors. IEEE trans. Image Processing, 15(4), 937-951, 2006).
(4) A plurality of image data are available (for example, Document 7: U.S. Pat. No. 6,470,097).
On the basis of a model assuming that input image data is obtained by applying the PSF to clear original image data, all the methods listed above estimate the original image data from the input image data. If the PSF is unknown in advance, the PSF is also to be estimated. This problem is called blind image deconvolution/restoration. Documents 1 to 3, described above, disclose techniques for blind deconvolution for the PSF that is uniform in the whole image data.
Document 4 discloses a technique of dividing an image into rectangles and performs a blur estimation on an assumption that the PSF is uniform within each rectangle; the technique can deal with a nonuniform PSF provided that the PSF varies slowly over an image.
Document 5 restores image data by acquiring the PSF from a sensor. Even if the PSF is available or is known in advance, deblurring is generally an ill-posed problem. Deblurring tends to amplify noise. As a method for preventing noise amplification, Document 6 discloses a method for deblurring image data using a given uniform PSF which suppresses possible noise amplification by applying a prior distribution to a wavelet coefficient of an image.
Document 7 discloses a method of using a plurality of images.
Document 8 (U.S. Pat. No. 6,928,182) discloses a technique for edge sharpening by estimating a blur around an edge detected in single image data and moving a luminance value from one side to the other side of the edge.
Image data to be deblurred often satisfies none of the conditions (1) to (4).
If none of the conditions (1) to (4) are satisfied, using of the techniques in Documents 1 to 8 is difficult.
Document 4 uniformly divides the image data into rectangular areas independently of a content of image data (subject in the image data). This technique is thus effective if the blur varies slowly (moderately) in the image data.
However, if blur variation in the image data is large, for example, if the amount of blur varies among a plurality of subjects with arbitrary shapes in the image data, the using of the technique in Document 4 is difficult. If the blur variation in the image data is intense, it is difficult to use the techniques in Documents 1 to 3, which are based on the condition that the blur is uniform.
The technique in Document 6 requires that the PSF is uniform and given as input. It is difficult to directly apply the technique in Document 6 if the blur variation in the image data is large. Furthermore, the technique in Document 6 suppresses possible noise amplification associated with deblurring. However, a block pattern may appear in restored image data owing to a character of the wavelet transform. Much calculation time is required to compensate (correct) for the block pattern.
The main object of the technique in Document 8 is sharpening, and the technique is thus insufficient for deblurring.